Nordic AI
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AI Strategy15 Jan 20267 min read

From Idea to AI Prototype in 10 Days: Our Sprint Process Explained

A complete breakdown of how we run rapid AI prototyping sprints — the tools, the decisions, and why speed does not have to mean sloppy.

Mihhail

Mihhail

Project Manager, Nordic AI

Ten days from kickoff to a working, demonstrable AI prototype. It sounds aggressive. Every client who has gone through our sprint tells us the same thing afterwards: they expected corners to be cut. What they got instead was a process so structured that speed was the natural output, not a compromise.

/01

Days 1–2: Problem Definition and Architecture Decision

The most expensive mistake in AI development is building the wrong thing fast. We spend the first two days doing nothing but understanding the problem. What does success look like? What data exists? What integrations are required? What are the hard constraints? By day two, we have an architecture decision record and a clearly scoped prototype brief — and we have killed at least three ideas that seemed good on day one.

/02

Days 3–7: Build and Integration

The build phase is disciplined. We work in a single shared environment, with daily syncs at 9am and 4pm. We do not add features during the build. We do not refactor unless something is broken. Every decision that was not made in days 1–2 gets a 30-minute decision window and then we move on. Indecision is the enemy of a 10-day sprint.

  • Day 3: Core AI pipeline and data connectors
  • Day 4: Business logic and workflow integration
  • Day 5: Frontend and user-facing interface
  • Day 6: Integration testing and edge case handling
  • Day 7: Performance optimisation and load testing

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Days 8–10: Testing, Refinement, and Handover

We demo internally on day eight. We fix what is broken on day nine. On day ten, we demo to the client with documentation, a deployment guide, and a clear next-steps roadmap. The prototype is not a toy — it is a working system that can go to users immediately, or be iterated into production with a clear path forward.

The takeaway

Speed in AI development is a discipline, not a shortcut. Our sprint process works because it makes decisions once, builds systematically, and never confuses velocity with urgency. A 10-day prototype is not the end of the process — it is the most valuable possible beginning.

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